Investigação sobre aplicação de amostragem compassiva a sinais de áudio.

Abstract

Compressive sampling is a new framework that exploits sparsity of a signal in a transform domain to perform sampling below the Nyquist rate. In this work, we propose and study a new technique for lossy audio compression of real, non-sparse audio signals. The method is based on the Modified Discrete Cosine Transform as a sparse basis and on l-1 norm optimization for signal reconstruction. We evaluate audio compression perceptual quality with the objective measure PEAQ. The proposed method has low computational complexity, universality and can be implemented in hardware on the encoder side, making it attractive to applications with hardware limitations as wireless sensor networks.